There is a significant body of work related to the design of the optical processor assembly of optical correlators, and especially on the theory of designing the reference image filters that some correlators use. A typical scientific paper on a correlator describes a spot of light, or a three-dimensional plot of the spot, and does not solve any real problem. The large body of literature on reference filter design addresses optimization of a variety of internal correlator functions, such as light efficiency, but fails to address any optimization in terms of the application of a correlator to a real-world problem.
In addition, many correlation systems are known, for example those discussed in “OPTICAL PROCESSING”, by one prominent authority in the field, Anthony VanderLugt. Mr. VanderLugt teaches a variety of correlators. He also teaches the potential of post-processing of the correlation plane. Another recognized authority in the field, J. Horner, teachers a combination of one specific preprocessor and a correlator. However, to Applicant's knowledge, no one has sought to optimize correlator systems to produce a viable real-time correlation system that can efficiently acquire and track one or more objects of interest in real time.
The correlation systems discussed by Mr. VanderLugt are optical correlators, and the Applicant's system is based on a real-time digital correlator. An optical correlator uses a series of optical lenses, a laser, cameras, and spatial light modulators to perform correlation between a filter and an image. A digital correlator is completely implemented in digital hardware such as Field Programmable Gate Arrays (FPGAs) and Central Processing Units (CPUs). A camera or other sensor is used to acquire and convert to digital form an image, and then all further processing is done digitally. Optical based correlators are notoriously hard to align and maintain because of the extreme alignment requirements for them to function properly. Optical correlators also require an assembly of optical and electronic elements to function properly, which can be difficult to build into a system for the military or for use in space. On the other hand, digital correlators can be implemented simply as a camera and a digital circuit card assembly. They also require no tedious alignment for proper operation.
Many practical applications of a correlator, such as an image recognition and tracking capability, require continuous, real-time tracking of the location of the recognized target or object of interest, for example tracking of an aircraft or missile in flight, or an automated docking maneuver between two spacecraft. Recognition capability requires that the correlator system provide, in real time, the parameters of range, bearing and orientations of the object of interest such as roll, pitch and yaw. In addition, it is desirable that the correlation system provides feedback to the camera or other sensor in order to control at least contrast, gamma, gain and brightness of the obtained image in order to maximize correlation peaks. In some instances it is further desirable to provide feedback related to camera direction control or pointing of the camera, such as pan and tilt or maneuvering of an object or spacecraft, in order to automatically maintain the object or view of interest generally centered in the field of view of the camera. Where docking maneuvers are undertaken, the camera or cameras providing imagery may be fixed to the apparatus or spacecraft, and the entire apparatus or spacecraft moved to maintain a view of the target. In other applications, a camera or other sensor mounted to a spacecraft may be mounted on some form of apparatus, such as a gimbal, that allows the camera to be moved to maintain a view of the object or field of view of interest.
Presently developed video processing systems and algorithms that measure distance, direction and orientation of an object typically have required a special cooperative target to be placed on the object of interest to aid in acquisition and tracking. These algorithms must be provided with very specific features, such as edges or spots in a particular pattern, in order to be successful. However, relying on a very specific feature for successful tracking is very limiting, especially with respect to spacecraft already in orbit due to inability to retrofit the spacecraft with the desired targeting markings or features.
Some systems also require large databases of correlation filters consisting of all possible target views that might be imaged by the sensor, to properly determine distance, direction and orientation of the target. However, such large databases of correlation filters requires a correspondingly large memory store of filters, which may require thousands to hundreds of thousands of filters. Such a large filter library is generally unfeasible with respect to available memory on a spacecraft, and requires significant lengths of time to search through in order to find the appropriate filter. Such a system in general is not feasible for spacecraft docking and other applications due to inability to provide real-time correlation information and the requirement for large filter stores.